Improving the COCOMO model using a neuro-fuzzy approach
β Scribed by Xishi Huang; Danny Ho; Jing Ren; Luiz F. Capretz
- Publisher
- Elsevier Science
- Year
- 2007
- Tongue
- English
- Weight
- 229 KB
- Volume
- 7
- Category
- Article
- ISSN
- 1568-4946
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## Abstract A methodology is proposed for constructing a flood forecast model using the adaptive neuroβfuzzy inference system (ANFIS). This is based on a selfβorganizing ruleβbase generator, a feedforward network, and fuzzy control arithmetic. Given the rainfallβrunoff patterns, ANFIS could systema
## Abstract Simple methods for calculating well losses are important for well design and optimization of groundwater source operation. Well losses arise from both laminar flow within the aquifer and turbulent flow within the well, and are often ignored in theoretical aquifer test analysis. The Jaco
## Abstract Correct estimation of sediment volume carried by a river is very important for many water resources projects. Conventional sediment rating curves, however, are not able to provide sufficiently accurate results. In this paper, a fuzzy logic approach is proposed to estimate suspended sedi